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Using a Bilingual Context in Word-Based Statistical Machine Translation

10 years 1 months ago
Using a Bilingual Context in Word-Based Statistical Machine Translation
Abstract. In statistical machine translation, phrase-based translation (PBT) models lead to a significantly better translation quality over single-word-based (SWB) models. PBT models translate whole phrases, thus considering the context in which a word occurs. In this work, we propose a model which further extends this context beyond phrase boundaries. The model is compared to a PBT model on the IWSLT 2007 corpus. To profit from the respective advantages of both models, we use a model combination, which results in an improvement in translation quality on the examined corpus.
Christoph Schmidt, David Vilar, Hermann Ney
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2008
Where PRIS
Authors Christoph Schmidt, David Vilar, Hermann Ney
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